Conventional optical navigation sensors use a pixel array with uniformly sized pixels to obtain digital images for computing motion. However, there is no optimal pixel size for resolving the features of all types of surfaces or imaged scenes.
For optical mouse sensors, a typical imaged scene is a surface such as a desktop or a mouse pad. Since there are several types of surfaces, different pixel arrays perform differently on each type of surface. For example, larger pixel sizes allow for greater light sensitivity for operation on dark surfaces. Larger pixel sizes are not optimal, though, for surfaces with small features because pixel arrays with larger pixel sizes do not have the proper resolution for such surfaces. As another example, some highly repetitive surfaces such as halftones can cause tracking errors if the pixel pitch is such that motion cannot be distinguished from the repetition of the pattern.
Thus, conventional optical navigation sensors do not easily adapt to different types of scenes imaged for computing motion. In particular, the characteristics of the conventional pixel arrays are fixed and do not provide optimal functionality with a variety of imaged scenes.